TY - JOUR
T1 - Curved neuromorphic image sensor array using a MoS2-organic heterostructure inspired by the human visual recognition system
AU - Choi, Changsoon
AU - Leem, Juyoung
AU - Kim, Min Sung
AU - Taqieddin, Amir
AU - Cho, Chullhee
AU - Cho, Kyoung Won
AU - Lee, Gil Ju
AU - Seung, Hyojin
AU - Bae, Hyung Jong
AU - Song, Young Min
AU - Hyeon, Taeghwan
AU - Aluru, Narayana R.
AU - Nam, Sung Woo
AU - Kim, Dae Hyeong
N1 - Funding Information:
This research was supported by IBS-R006-A1. S.N. acknowledges support from NSF (MRSEC DMR-1720633, ECCS-1935775, CMMI-1904216, and DMR-1708852), AFOSR (FA2386-17-1-4071), NASA ECF (NNX16AR56G), and ONR YIP (N00014-17-1-2830). N.R.A. acknowledges support from NSF (OISE-1545907, DMR-1708852, MRSEC DMR-1720633, and CMMI-1921578). A.T. and N.R.A. acknowledge the use of the parallel computing resources: (1) Blue Waters (supported by NSF awards OCI-0725070, ACI-1238993 and the state of Illinois, and as of December 2019, supported by the National Geospatial-Intelligence Agency), and (2) Comet at San Diego Supercomputer Center which is provided by the Extreme Science and Engineering Discovery Environment (XSEDE) (supported by National Science Foundation (NSF) Grant No. OCI1053575) under TG-CDA100010 allocation. C.C. acknowledges support from NASA Space Technology Research Fellow Grant No. 80NSSC17K0149.
Publisher Copyright:
© 2020, The Author(s).
PY - 2020/12
Y1 - 2020/12
N2 - Conventional imaging and recognition systems require an extensive amount of data storage, pre-processing, and chip-to-chip communications as well as aberration-proof light focusing with multiple lenses for recognizing an object from massive optical inputs. This is because separate chips (i.e., flat image sensor array, memory device, and CPU) in conjunction with complicated optics should capture, store, and process massive image information independently. In contrast, human vision employs a highly efficient imaging and recognition process. Here, inspired by the human visual recognition system, we present a novel imaging device for efficient image acquisition and data pre-processing by conferring the neuromorphic data processing function on a curved image sensor array. The curved neuromorphic image sensor array is based on a heterostructure of MoS2 and poly(1,3,5-trimethyl-1,3,5-trivinyl cyclotrisiloxane). The curved neuromorphic image sensor array features photon-triggered synaptic plasticity owing to its quasi-linear time-dependent photocurrent generation and prolonged photocurrent decay, originated from charge trapping in the MoS2-organic vertical stack. The curved neuromorphic image sensor array integrated with a plano-convex lens derives a pre-processed image from a set of noisy optical inputs without redundant data storage, processing, and communications as well as without complex optics. The proposed imaging device can substantially improve efficiency of the image acquisition and recognition process, a step forward to the next generation machine vision.
AB - Conventional imaging and recognition systems require an extensive amount of data storage, pre-processing, and chip-to-chip communications as well as aberration-proof light focusing with multiple lenses for recognizing an object from massive optical inputs. This is because separate chips (i.e., flat image sensor array, memory device, and CPU) in conjunction with complicated optics should capture, store, and process massive image information independently. In contrast, human vision employs a highly efficient imaging and recognition process. Here, inspired by the human visual recognition system, we present a novel imaging device for efficient image acquisition and data pre-processing by conferring the neuromorphic data processing function on a curved image sensor array. The curved neuromorphic image sensor array is based on a heterostructure of MoS2 and poly(1,3,5-trimethyl-1,3,5-trivinyl cyclotrisiloxane). The curved neuromorphic image sensor array features photon-triggered synaptic plasticity owing to its quasi-linear time-dependent photocurrent generation and prolonged photocurrent decay, originated from charge trapping in the MoS2-organic vertical stack. The curved neuromorphic image sensor array integrated with a plano-convex lens derives a pre-processed image from a set of noisy optical inputs without redundant data storage, processing, and communications as well as without complex optics. The proposed imaging device can substantially improve efficiency of the image acquisition and recognition process, a step forward to the next generation machine vision.
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U2 - 10.1038/s41467-020-19806-6
DO - 10.1038/s41467-020-19806-6
M3 - Article
C2 - 33230113
AN - SCOPUS:85096432334
VL - 11
JO - Nature Communications
JF - Nature Communications
SN - 2041-1723
IS - 1
M1 - 5934
ER -